Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China.
Department of Public Health and Health Management, Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan, Shandong, China.
Eur J Clin Nutr. 2022 Sep;76(9):1309-1314. doi: 10.1038/s41430-022-01106-5. Epub 2022 Mar 8.
Previous observational studies focused on the association of serum magnesium (SMg) and chronic kidney disease (CKD), but the conclusion was inconsistent. To investigate the causal relationship of SMg and CKD, we performed a two-sample mendelian randomization (TSMR) analysis using publicly datasets.
In mendelian randomization (MR) analysis, we used single nucleotide polymorphisms (SNPs) which had genetic statistical significance with SMg but not associated with kidney function and confounding factors as instrumental variable (IV). To select SNPs, we used publicly database of Genome Wide Association Study (GWAS) and Chronic Kidney Disease Genetics (CKDGen) Confirms. We used inverse-variance weighted (IVW), weighted median, MR-Egger regression, weighted mode, and simple mode approaches in TSMR analysis.
We selected 4 SNPs (rs4072037, rs7965584, rs11144134 and rs448378) as IV. In IVW approach, the result of MR analysis for CKD was OR = 0.55, 95% CI: 0.06, 4.75, P = 0.58; for estimated glomerular filtration rate from creatinine (eGFR)crea was β = -0.06, 95% CI: -1.08, 0.07, P = 0.39; for estimated glomerular filtration rate from cystatin C (eGFR)cys was β = -0.03, 95% CI: -0.43, 0.36, P = 0.86, respectively per SD increase in SMg. When subgroup by diabetes mellitus (DM), the results for DM-eGFRcrea was β = -0.33, 95% CI: -0.85, 0.19, P = 0.21; and for non-DM-eGFRcrea was β = -0.03, 95% CI: -0.16, 0.11, P = 0.71. The results of other four MR approaches were consistent with IVW approach (all P > 0.05).
Our TSMR analysis showed that SMg had no causal effect on kidney function and progress CKD in European descent. As for the results about overall population, the verified study is needed in future study.
先前的观察性研究集中于血清镁(SMg)与慢性肾脏病(CKD)之间的关联,但结论不一致。为了研究 SMg 与 CKD 的因果关系,我们使用公开数据集进行了两样本 Mendelian 随机化(TSMR)分析。
在 Mendelian 随机化(MR)分析中,我们使用与 SMg 具有遗传统计学意义但与肾功能和混杂因素无关的单核苷酸多态性(SNP)作为工具变量(IV)。为了选择 SNP,我们使用了全基因组关联研究(GWAS)和慢性肾脏病遗传学(CKDGen)确认的公共数据库。我们在 TSMR 分析中使用了逆方差加权(IVW)、加权中位数、MR-Egger 回归、加权模式和简单模式方法。
我们选择了 4 个 SNP(rs4072037、rs7965584、rs11144134 和 rs448378)作为 IV。在 IVW 方法中,MR 分析结果显示 CKD 的 OR=0.55,95%CI:0.06,4.75,P=0.58;估算肾小球滤过率(eGFR)crea 的β=−0.06,95%CI:−1.08,0.07,P=0.39;估算肾小球滤过率(eGFR)cys 的β=−0.03,95%CI:−0.43,0.36,P=0.86,SMg 每增加一个标准差。当按糖尿病(DM)进行亚组分析时,DM-eGFRcrea 的结果为β=−0.33,95%CI:−0.85,0.19,P=0.21;而非 DM-eGFRcrea 的结果为β=−0.03,95%CI:−0.16,0.11,P=0.71。其他四种 MR 方法的结果与 IVW 方法一致(均 P>0.05)。
我们的 TSMR 分析表明,SMg 对肾功能和慢性肾脏病进展没有因果影响。对于总体人群的结果,需要在未来的研究中进行验证。